Recovery of Phenotypes Obtained by Adaptive Evolution through Inverse Metabolic Engineering
Bibliographic record
Abstract
In a previous study, system level analysis of adaptively evolved yeast mutants showing improved galactose utilization revealed relevant mutations. The governing mutations were suggested to be in the Ras/PKA signaling pathway and ergosterol metabolism. Here, site-directed mutants having one of the mutations RAS2(Lys77), RAS2(Tyr112), and ERG5(Pro370) were constructed and evaluated. The mutants were also combined with overexpression of PGM2, earlier proved as a beneficial target for galactose utilization. The constructed strains were analyzed for their gross phenotype, transcriptome and targeted metabolites, and the results were compared to those obtained from reference strains and the evolved strains. The RAS2(Lys77) mutation resulted in the highest specific galactose uptake rate among all of the strains with an increased maximum specific growth rate on galactose. The RAS2(Tyr112) mutation also improved the specific galactose uptake rate and also resulted in many transcriptional changes, including ergosterol metabolism. The ERG5(Pro370) mutation only showed a small improvement, but when it was combined with PGM2 overexpression, the phenotype was almost the same as that of the evolved mutants. Combination of the RAS2 mutations with PGM2 overexpression also led to a complete recovery of the adaptive phenotype in galactose utilization. Recovery of the gross phenotype by the reconstructed mutants was achieved with much fewer changes in the genome and transcriptome than for the evolved mutants. Our study demonstrates how the identification of specific mutations by systems biology can direct new metabolic engineering strategies for improving galactose utilization by yeast.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".